Metode dan Algoritma Dalam Data Clustering: Systematic Literature Review

Authors

  • Dian Restu Adji Universitas Dian Nuswantoro
  • Erba Lutfina Universitas Nasional Karangturi
  • Bhekti Eka Ferdianto Universitas Dian Nuswantoro
  • Eva Prashanti Universitas Dian Nuswantoro
  • Kenza Amelia Putri Anwarri Universitas Dian Nuswantoro
  • Syahrul Rizqi Prayogo Universitas Dian Nuswantoro

DOI:

https://doi.org/10.53416/stmj.v5i1.326

Keywords:

systematic literature review, Data Mining, data clustering

Abstract

This study is Systematic Literature Review (SLR) of 34 journals related to data grouping techniques (clustering). The main objective of the study is to investigate the use of clustering methods in various research fields. In order to achieve this goal, this study answers five main research questions. First, this study analyzes research fields where clustering methods are often used in data mining applications. Second, this study identifies the most frequently used clustering methods based on data from the journals that have been collected. Third, this study determines the clustering method that provides the most optimal number of groups (clustering) based on the analysis of these journals. Fourth, this study identifies the types of data sets that are most often used in the context of clustering. Finally, this study looks at the distribution of the publication years of these journals to present a time frame of the development of clustering research. The results of this study provide in-depth insight into the trend of the use of clustering methods in various research contexts, provide information on the most commonly used methods, identify methods that provide optimal results, describe the dominant types of data sets, and provide a chronological perspective on the development of clustering research. These findings can provide valuable guidance for researchers interested in applying or developing clustering methods in specific fields.

Author Biography

Erba Lutfina, Universitas Nasional Karangturi

 

 

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Published

2025-01-31

Issue

Vol. 5 No. 1 (2025): Januari 2025

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Articles

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